Towards Hierarchical Classification of Data Streams

  • Antonio Rafael Sabino ParmezanEmail author
  • Vinicius M. A. Souza
  • Gustavo E. A. P. A. Batista
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11401)


In data stream mining, state-of-the-art machine learning algorithms for the classification task associate each event with a class belonging to a finite, devoid of structural dependencies and usually small, set of classes. However, there are more complex dynamic problems where the classes we want to predict make up a hierarchal structure. In this paper, we propose an incremental method for hierarchical classification of data streams. We experimentally show that our stream hierarchical classifier present advantages to the traditional online setting in three real-world problems related to entomology, ichthyology, and audio processing.


Hierarchical classification Data streams Online learning 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Antonio Rafael Sabino Parmezan
    • 1
    Email author
  • Vinicius M. A. Souza
    • 1
  • Gustavo E. A. P. A. Batista
    • 1
  1. 1.Instituto de Ciências Matemáticas e de Computação, Universidade de São PauloSão CarlosBrazil

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